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  2. Linear search - Wikipedia

    en.wikipedia.org/wiki/Linear_search

    In computer science, linear search or sequential search is a method for finding an element within a list. It sequentially checks each element of the list until a match is found or the whole list has been searched. [1] A linear search runs in linear time in the worst case, and makes at most n comparisons, where n is the length of

  3. Search algorithm - Wikipedia

    en.wikipedia.org/wiki/Search_algorithm

    Search algorithms can be made faster or more efficient by specially constructed database structures, such as search trees, hash maps, and database indexes. [1] [2] Search algorithms can be classified based on their mechanism of searching into three types of algorithms: linear, binary, and hashing. Linear search algorithms check every record for ...

  4. Line search - Wikipedia

    en.wikipedia.org/wiki/Line_search

    In optimization, line search is a basic iterative approach to find a local minimum of an objective function:. It first finds a descent direction along which the objective function f {\displaystyle f} will be reduced, and then computes a step size that determines how far x {\displaystyle \mathbf {x} } should move along that direction.

  5. Linear search problem - Wikipedia

    en.wikipedia.org/wiki/Linear_search_problem

    This problem is usually called the linear search problem and a search plan is called a trajectory. The linear search problem for a general probability distribution is unsolved. [ 5 ] However, there exists a dynamic programming algorithm that produces a solution for any discrete distribution [ 6 ] and also an approximate solution, for any ...

  6. Wolfe conditions - Wikipedia

    en.wikipedia.org/wiki/Wolfe_conditions

    Each step often involves approximately solving the subproblem (+) where is the current best guess, is a search direction, and is the step length. The inexact line searches provide an efficient way of computing an acceptable step length α {\displaystyle \alpha } that reduces the objective function 'sufficiently', rather than minimizing the ...

  7. Jump search - Wikipedia

    en.wikipedia.org/wiki/Jump_search

    To find the exact position of the search key in the list a linear search is performed on the sublist L [(k-1)m, km]. The optimal value of m is √ n, where n is the length of the list L. Because both steps of the algorithm look at, at most, √ n items the algorithm runs in O(√ n) time. This is better than a linear search, but worse than a ...

  8. Prune and search - Wikipedia

    en.wikipedia.org/wiki/Prune_and_search

    As such, it is a form of decrease and conquer algorithm, where at each step the decrease is by a constant factor. Let n be the input size, T(n) be the time complexity of the whole prune-and-search algorithm, and S(n) be the time complexity of the pruning step. Then T(n) obeys the following recurrence relation:

  9. Interior-point method - Wikipedia

    en.wikipedia.org/wiki/Interior-point_method

    An interior point method was discovered by Soviet mathematician I. I. Dikin in 1967. [1] The method was reinvented in the U.S. in the mid-1980s. In 1984, Narendra Karmarkar developed a method for linear programming called Karmarkar's algorithm, [2] which runs in provably polynomial time (() operations on L-bit numbers, where n is the number of variables and constants), and is also very ...